#Lagos download script
#lagosne_get(dest_folder = LAGOSNE:::lagos_path(),overwrite=T)
#Load in lagos
lagos <- lagosne_load()
## Warning in (function (version = NULL, fpath = NA) : LAGOSNE version unspecified,
## loading version: 1.087.3
#Grab the lake centroid info
lake_centers <- lagos$locus
# Make an sf object
spatial_lakes <- st_as_sf(lake_centers,coords=c('nhd_long','nhd_lat'),
crs=4326)
#Grab the water quality data
nutr <- lagos$epi_nutr
#Look at column names
#names(nutr)
clarity_only <- nutr %>%
select(lagoslakeid,sampledate,chla,doc,secchi) %>%
mutate(sampledate = as.character(sampledate) %>% ymd(.))
#Look at the number of rows of dataset
#nrow(clarity_only)
chla_secchi <- clarity_only %>%
filter(!is.na(chla),
!is.na(secchi))
# How many observatiosn did we lose?
filteredObservations = nrow(clarity_only) - nrow(chla_secchi)
# Keep only the lakes with at least 200 observations of secchi and chla
chla_secchi_200 <- chla_secchi %>%
group_by(lagoslakeid) %>%
mutate(count = n()) %>%
filter(count > 200)
We lost 651095 observations because they were missing Secchi or Chlorophyll data.
spatial_200 <- inner_join(spatial_lakes,chla_secchi_200 %>%
distinct(lagoslakeid,.keep_all=T),
by='lagoslakeid')
### Take the mean chl_a and secchi by lake
mean_values_200 <- chla_secchi_200 %>%
# Take summary by lake id
group_by(lagoslakeid) %>%
# take mean chl_a per lake id
summarize(mean_chla = mean(chla,na.rm=T),
mean_secchi=mean(secchi,na.rm=T)) %>%
#Get rid of NAs
filter(!is.na(mean_chla),
!is.na(mean_secchi)) %>%
# Take the log base 10 of the mean_chl
mutate(log10_mean_chla = log10(mean_chla))
#Join datasets
mean_spatial <- inner_join(spatial_lakes,mean_values_200,
by='lagoslakeid')
#Make a map
mapview(mean_spatial,zcol='log10_mean_chla')
Here, I just want a plot of chla vs secchi for all sites
#Your code here
ggplot(mean_values_200) +
geom_point(aes( mean_secchi, mean_chla))
ggplot(chla_secchi) +
geom_point(aes( secchi, chla))
Chlorophyll is used for photosynthesis. Light is required as an input. As depth below the surface increases light decreases. Additionally deeper lakes tend to produce less photosynthetic allgy due to increased mechanical mixing of diffrent water layers.
## Get count for each lake
lago_summary = chla_secchi %>%
#slice(1:10000) %>%
group_by(lagoslakeid) %>%
summarize(
mean_chla = mean(chla,na.rm=T),
mean_secchi=mean(secchi,na.rm=T),
count=n()
)
## Join to lake location
lago_location_summary =
merge(
x = lago_summary,
y = lake_centers,
by = "lagoslakeid",
all.x = TRUE
) %>%
st_as_sf(coords=c('nhd_long','nhd_lat'),crs=4326)
mapview(lago_location_summary)